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  • Blanchy_et_al(Author copy)

    Rights statement: This is the author’s version of a work that was accepted for publication in Computers & Geosciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Geosciences, 137, 2020 DOI: 10.1016/j.cageo.2020.104423

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    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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ResIPy, an intuitive open source software for complex geoelectrical inversion/modeling

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Published
Article number104423
<mark>Journal publication date</mark>1/04/2020
<mark>Journal</mark>Computers and Geosciences
Volume137
Number of pages12
Publication StatusPublished
Early online date4/02/20
<mark>Original language</mark>English

Abstract

Electrical resistivity tomography (ERT) and induced polarization (IP) methods are now widely used in many interdisciplinary projects. Although field surveys using these methods are relatively straightforward, ERT and IP data require the application of inverse methods prior to any interpretation. Several established non-commercial inversion codes exist, but they typically require advanced knowledge to use effectively. ResIPy was developed to provide a more intuitive, user-friendly, approach to inversion of geoelectrical data, using an open source graphical user interface (GUI) and a Python application programming interface (API). ResIPy utilizes the mature R2/cR2 inversion codes for ERT and IP, respectively. The ResIPy GUI facilitates data importing, data filtering, error
modeling, mesh generation, data inversion and plotting of inverse models. Furthermore, the easy to use designof ResIPy and the help provided inside makes it an effective educational tool. This paper highlights the rationale and structure behind the interface, before demonstrating its capabilities in a range of environmental problems. Specifically, we demonstrate the ease at which ResIPy deals with topography, advanced data processing, the ability to fix and constrain regions of known geoelectrical properties, time-lapse analysis and the capability for forward modeling and survey design.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Computers & Geosciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Geosciences, 137, 2020 DOI: 10.1016/j.cageo.2020.104423